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      Is Open Access A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

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          Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae. In particular, allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner.

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          Most cited references 23

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          Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

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            Functional profiling of the Saccharomyces cerevisiae genome.

            Determining the effect of gene deletion is a fundamental approach to understanding gene function. Conventional genetic screens exhibit biases, and genes contributing to a phenotype are often missed. We systematically constructed a nearly complete collection of gene-deletion mutants (96% of annotated open reading frames, or ORFs) of the yeast Saccharomyces cerevisiae. DNA sequences dubbed 'molecular bar codes' uniquely identify each strain, enabling their growth to be analysed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays. We show that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment. Less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal growth in four of the tested conditions. Our results validate the yeast gene-deletion collection as a valuable resource for functional genomics.
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              Global analysis of protein localization in budding yeast.

              A fundamental goal of cell biology is to define the functions of proteins in the context of compartments that organize them in the cellular environment. Here we describe the construction and analysis of a collection of yeast strains expressing full-length, chromosomally tagged green fluorescent protein fusion proteins. We classify these proteins, representing 75% of the yeast proteome, into 22 distinct subcellular localization categories, and provide localization information for 70% of previously unlocalized proteins. Analysis of this high-resolution, high-coverage localization data set in the context of transcriptional, genetic, and protein-protein interaction data helps reveal the logic of transcriptional co-regulation, and provides a comprehensive view of interactions within and between organelles in eukaryotic cells.

                Author and article information

                [* ]The Donnelly Centre, University of Toronto, Ontario M5S 3E1, Canada
                []Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, Minnesota 55455
                []Simons Center for Data Analysis, Simons Foundation, New York, New York 10010
                [§ ]Lewis-Sigler Institute for Integrative Genomics, Princeton University, New Jersey 08544
                [** ]Department of Molecular Genetics, University of Toronto, Ontario M5S 3E1
                Author notes
                [1 ]Corresponding authors: Department of Computer Science and Engineering, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455. E-mail: cmyers@ ; and The Donnelly Centre, University of Toronto, 160 College Street, Room 13212, Toronto, ON M5S 3E1, Canada. E-mail: michael.costanzo@ ; brenda.andrews@ ; and charlie.boone@
                G3 (Bethesda)
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                20 March 2017
                May 2017
                : 7
                : 5
                : 1539-1549
                Copyright © 2017 Usaj et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Figures: 8, Tables: 0, Equations: 0, References: 25, Pages: 11


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